The invention relates to a method for association of 2D measurements from a sensor system, in particular for air defense.
EP 0 205 794 A1 discloses a surveillance system such as this for space/airspace surveillance. The real targets which are produced as video signals by an IR position-finding appliance during each search cycle are preprocessed in a data preprocessing device, and are discriminated and stored in an IR signal processor on the basis of their elevation values and azimuth values. The real-target coordinates in elevation, azimuth and distance, as determined by the appliances, are supplied to a higher-level fire control facility.
A radar measurement device for airspace monitoring is disclosed in DE 1 057 788. A 2D pulse-Doppler radar is described in DE 36 88 935 T2. DE 39 26 216 A1 discloses a multifunction radar. A secondary radar system is published in DE 41 09 981 A1.
A method for airspace surveillance of a relatively large region with the aid of pulse surveillance radars has already been disclosed in DE-PS 977 646.
DE 198 56 231 A1 discloses a method for aircraft surveillance, which is carried out using satellites. DE 100 32 433 A1 also deals with a method for space surveillance. DE 36 37 129 C2 discloses a three-way DME system for attempting to find the position of an aircraft.
If the sensors and the fire control equipment are networked, they can interchange their current target status measurements (position and velocity) with one another and/or can send the measurements to a preferably central computer. In order to create the instantaneous air situation, the received signals from the respective fire control equipments are investigated to determine whether they originate from the same or from different targets. Once the measurements that have been received in a time interval have been associated, a decision is made as to how many targets have been recorded in an airspace, which and how many of them are new, and which and how many known targets have an updated state. In particular, it is difficult to associate targets that are flying physically closely together using known methods. Measurement errors relating to the position and velocity of a target are a major disturbance source for correct association. The errors generally occur during the measurement process or during a necessary time matching process, which is done by means of extrapolation to a common time, for comparison with other measurements. Measurement errors increase the probability of incorrect associations. The further aspect for errors occurs, as already mentioned, in the spatial resolution of the known 2D, 2.5D sensors which cannot resolve one of the three spatial dimensions at all, or can resolve it only inadequately. For example, in the case of a 2D search radar, only the range and azimuth of a target with respect to the sensor are measured, while in contrast there is no information about the elevation. In the case of 2.5D search radars, the elevation area of the target is restricted to an interval. In contrast, passive electro-optical sensors produce measurements of azimuth and elevation, but cannot measure the range to the target.
In order to allow the measurements to be compared, they must be converted to a common, higher-level coordinate system. A local 2D measurement can be transformed to a different three-dimensional coordinate system only by assuming the third dimension. This results in a further increase in the measurement inaccuracy, because of a high measurement uncertainty. Measurements such as these are in general distinguishable only with difficulty, thus exacerbating the association process.
The time required for association is a further factor, in addition to the technical problems relating to accuracy and resolution. In the case of large networked air-defense systems, which monitor an airspace with intensive targets, the association process leads to a computation complexity and time penalty which allows only a very low level of updating.
DE 44 39 742 C2 proposes a method for automatic combinational optimization of associations for tracking a plurality of moving objects. A new association matrix is generated on the basis of a more or less randomly selected, undefined, but valid association matrix. A check is then carried out to determine whether this matrix represents a better solution than the old association matrix. If this is the case, this matrix is adopted as the new starting point for a further search. The aim of this method is to avoid time-consuming searching and to achieve adequate quality.